the connection between artificial intelligent, machine learning and data mining? - phdassistance.com

THE CONNECTION BETWEENARTIFICIAL INTELLIGENT,MACHINE LEARNING ANDDATA MINING

An Academic presentation byDr. Nancy Agens, Head, Technical Operations, PhdassistanceGroup  www.phdassistance.comEmail: info@phdassistance.com

In Brief

Introduction

Artificial Intelligence(AI)

Difference Between AI and ML

Interlinking “Data Mining” (DM) with AI and ML

Similarity between ML and DM

Similarity between AI and DM

Conclusion

Future Scopes

Outline

TODAY'S DISCUSSION

One of the booming subjects inside the fields of Science andTechnology include Artificial Intelligence (AI). The power of

Artificial Intelligence is unbelievable. Even professionalexperts such as Elon Musk, Stephen Hawking, etc. Before

jumping into the Topic, here is an interesting fact aboutartificial intelligence.

In Brief

There was a workshop conducted as ‘Dartmouth Summer Research Project’ in 1956.

This program involved the participation of various experts, language professionals,analysts, budding scholars, and the like.

In this event, John McCarthy was the person who coined the term ‘ArtificialIntelligence’, in the stance of clarifying queries regarding a “thinking machine.”

Now, moving onto to topic, let us quickly grasp the definition of Artificial Intelligence.

Introduction

Developing the intelligence code of a machine is artificial intelligence.

Artificial Intelligence is paramount to the development of many online and offlineindustries such as medicine, food production, engineering, biochemistry, psychology,neuroscience, physics, and the list goes on.

Learning is a methodical process, whereby a person puts his or her fullest efforts tounderstand, read or write a concept, and memorize it for future purpose.

Machine learning(ML) and artificial intelligence go hand-in-hand.

To put it straight, machine learning is a sub-component under some optimizedfunctions of AI.

Artificial Intelligence(AI)

Media and marketing professionalsrefer to the term ArtificialIntelligence over machine learning.

Difference Between AI and ML

if a media person speaks of expertsystems, deep learning or processautomation, they are referring tomachine learning.

Artificial Intelligence and Machine Learning are both subsets and interrelated.

Artificial Intelligence (AI) Machine Learning (ML)

Contd..

AI means wisdom and highintelligence.

Proficiency in ML means gainingknowledge.

The core focus or objective ofArtificial Intelligence is to increasethe chances of success rate (level).

Machine learning protocolstarget more about the accuracyin results.

Artificial Intelligence (AI) Machine Learning (ML)

Artificial intelligence is a technologythat focusses on developingcomputational techniques to solvereal-life problems.

Meaning, ML concerns more aboutlearning processes through data.

Knowledge discovery is a simple term to refer to the process of data mining.

The science of deriving and extracting information pieces and data from alarge set of data is data mining.

More of collection, analyzation, storage, movement, storage and retrieval,mining this data has a close relation to both AI and ML.

Interlinking “Data Mining” (DM) with AI and ML

The major similarity between machine learning and data mining is in itsdevelopmental pattern.

Data analysis and pattern recognition are 2 vital technologies that canchange the way data mining concepts are handled by platforms.

And for this, data mining applications can be developed only through thetechniques of ML.

Similarity between ML and DM

When the system identifies relevant information from its previously knowninformation factory, then data mining works based on AI’s experiencealgorithms.

Financial industries and domains that involve more of money-relatedaspects such as insurance, consider the 3 technologies togethercomparatively. (AI + ML + DM)

Similarity between AI and DM

AI is a growing solid technology which has the potentialand skill to even turn a fantasy into the reality world.

The 3 buzzwords, artificial intelligence, machine learning,data mining, together will have the power to control evenhuman brains in the upcoming eras without our insight.

Do not take leverage as both constructive and destructiveresults can occur from the misuse of technology ineveryone’s life!

Conclusion

You would have read technologies such as 5G, Tesla, smart grid, roboticsurgery, and the like in various journals and articles.

But think about the one commonality they all own – Artificial Intelligence.

From the Research on Biomedical neurons to the study on Mechanical andElectrical Engineering, we are about to witness a livelihood, that would befaster, better, efficient, safe and productive.

Future Scopes

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